Music Stimuli Recognition in Electroencephalogram Signal
Keywords:Artificial neural networks, Brain-computer interfaces, Digital filtering, Electroencephalography.
When humans are listening to music they perceive beats, rhythms and melodies. Music stimuli induce motor system activities and it has a powerful emotion trigger effect. Since music is a potential stimulus in electroencephalogram based emotion research we supposed that different kinds of songs are recognizable from electroencephalogram signal. In this study we try to recognize music-induced electroencephalogram responses with the popular Neurosky Mindwave device. This paper describes the test conditions and the efficiency of an artificial neural network in combination with different data pre-processing techniques. The final outcomes show the negative effect of frequency decomposition and that the meditation level has more significant effect on the recognition than a particular song.
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